1. Field
The present disclosure relates to electronics and more particularly to techniques for sensitivity improvement in a wireless communication device, system or network.
2. Background
A key target in the evolution of mobile communication is to achieve ever higher end-user data rates. While higher peak data rates are desirable, equally desirable are higher data rates over an entire cell area, including, for example, users at a cell edge.
Data rate and channel capacity go hand-in-hand. A channel's capacity is the maximum rate that information can be transferred over a given communication channel. Although relatively complicated in the general case, for the special case of communication over a channel, e.g. a radio link, only impaired by additive white Gaussian noise, the channel capacity C is given by the relatively simple expression
                              C          =                      BW            ·                                          log                2                            ⁡                              (                                  1                  +                                      S                    N                                                  )                                                    ,                            Eq        .                                  ⁢                  (          1          )                    where BW is the bandwidth available for the communication, S denotes the received signal power, and N denotes the power of the white noise impairing the received signal.
Two fundamental factors limiting the achievable data rate are the available received signal power, or more generally the available signal-power-to-noise-power ratio S/N, and the available bandwidth. To further clarify how and when these factors limit the achievable data rate, assume communication with a certain information rate R. The received signal power can then be expressed as S=Eb□R where Eb is the received energy per information bit. Furthermore, the noise power can be expressed as N=N0□BW where N0 is the constant noise power spectral density measured in W/Hz.
Clearly, the information rate can never exceed the channel capacity. Together with the above expressions for the received signal power and noise power, this leads to the inequality:
                              R          ≤          C                =                              BW            ·                                          log                2                            ⁡                              (                                  1                  +                                      S                    N                                                  )                                              =                      BW            ·                                          log                2                            ⁡                              (                                  1                  +                                                                                    E                        b                                            ·                      R                                                                                      N                        0                                            ·                      BW                                                                      )                                                                        Equation        ⁢                                  ⁢                  (          2          )                    
or, by defining the radio-link bandwidth utilization γ R/BW,
                    γ        ≤                                            log              2                        ⁡                          (                              1                +                                  γ                  ·                                                            E                      b                                                              N                      0                                                                                  )                                .                                    Eq        .                                  ⁢                  (          3          )                    
This inequality can be reformulated to provide a lower bound on the required received energy per information bit, normalized to the noise power density, for a given bandwidth utilization γ
                                                        E              b                                      N              0                                ≥                      min            ⁢                          {                                                E                  b                                                  N                  0                                            }                                      =                                            2              ⁢              γ                        -            1                    γ                                    Eq        .                                  ⁢                  (          4          )                    
For bandwidth utilizations significantly less than one (that is for information rates substantially smaller than the utilized bandwidth) the minimum required Eb/N0 is relatively constant, regardless of γ. For a given noise power density, any increase of the information data rate then implies a similar relative increase in the minimum required signal power S=Eb·R at the receiver. On the other hand, for bandwidth utilizations larger than one the minimum required Eb/N0 increases rapidly with γ. Thus, in case of data rates in the same order as or larger than the communication bandwidth, any further increase of the information data rate, without a corresponding increase in the available bandwidth, implies a larger, eventually much larger, relative increase in the minimum required received signal power.
Basic conclusions can thus be drawn regarding the provisioning of higher data rates in a mobile-communication system when noise is the main source of radio-link impairment (a noise-limited scenario).
First, the data rates that can be provided in such scenarios are always limited by the available received signal power or, in the general case, the received signal-power-to-noise-power ratio. Furthermore, any increase of the achievable data rate within a given bandwidth will require at least the same relative increase of the received signal power. At the same time, if sufficient received signal power can be made available, basically any data rate can, at least in theory, be provided within a given limited bandwidth.
In case of low-bandwidth utilization, i.e., as long as the radio-link data rate is substantially lower than the available bandwidth, any further increase of the data rate requires approximately the same relative increase in the received signal power. This can be referred to as power-limited operation (in contrast to bandwidth-limited operation) where an increase in the available bandwidth does not substantially impact what received signal power is required for a certain data rate.
On the other hand, in case of high-bandwidth utilization, i.e. in case of data rates in the same order as or exceeding the available bandwidth, any further increase in the data rate requires a much larger relative increase in the received signal power unless the bandwidth is increased in proportion to the increase in data rate. This can be referred to as a bandwidth-limited operation since an increase in the bandwidth will reduce the received signal power required for a certain data rate. Thus, to make efficient use of the available received signal power or, in the general case, the available signal-to-noise ratio, the transmission bandwidth should at least be of the same order as the data rates to be provided.
Assuming a constant transmit power, the received signal power can always be increased by reducing the distance between the transmitter and the receiver, thereby reducing the attenuation of the signal as it propagates from the transmitter to the receiver.
Thus, in a noise-limited scenario it is at least in theory always possible to increase the achievable data rates, assuming that one is prepared to accept a reduction in the transmitter/receiver distance; that is a reduced range. In a mobile-communication system this would correspond to a reduced cell size and thus the need for more cell sites to cover the same overall area. Especially, providing data rates in the same order as or larger than the available bandwidth, i.e. with a high-bandwidth utilization, would require a significant cell-size reduction. Alternatively, one has to accept that the high data rates are only available for mobile terminals in the center of the cell, i.e. not over the entire cell area.
Another means to increase the overall received signal power for a given transmit power is the use of additional antennas at the receiver side, also known as receive-antenna diversity. Multiple receive antennas can be applied at the base station (that is for the uplink) or at the mobile terminal (that is for the downlink). By proper combining of the signals received at the different antennas, the signal-to-noise ratio after the antenna combining can be increased in proportion to the number of receive antennas, thereby allowing for higher data rates for a given transmitter/receiver distance.
Multiple antennas can also be applied at the transmitter side, typically at the base station, and be used to focus a given total transmit power in the direction of the receiver, i.e. toward the target mobile terminal. This will increase the received signal power and thus, once again, allow for higher data rates for a given transmitter/receiver distance.
However, providing higher data rates by the use of multiple transmit or receive antennas is only efficient up to a certain level, i.e. as long as the data rates are power limited rather than bandwidth limited. Beyond this point, the achievable data rates start to saturate and any further increase in the number of transmit or receive antennas, although leading to a correspondingly improved signal-to-noise ratio at the receiver, will only provide a marginal increase in the achievable data rates. This saturation in achievable data rates can be avoided though, by the use of multiple antennas at both the transmitter and the receiver, enabling what can be referred to as spatial multiplexing, often also referred to as MIMO (Multiple-Input Multiple-Output). However, MIMO techniques may increase the size and cost of a wireless device.
An alternative to increasing the received signal power (say by accepting a smaller cell size, or employing MIMO techniques), perhaps at significant cost, is to reduce the noise power, or more exactly the noise power density, at the receiver. This can, at least to some extent, be achieved by more advanced receiver RF design, allowing for a reduced receiver noise figure.
Reducing receiver noise figure is a great challenge. As portable electronic devices become increasingly miniaturized and multi-functional, internally generated noise becomes more of a problem both at the component level as well as within a handset (i.e. system level). Noise has the potential to adversely affect circuit components through electromagnetic interference (EMI). Prior attempts to address EMI problems have traditionally focused on debugging a prototype, modifying the floor plan and system layout, and improving shielding—all of which come at significant cost, in terms of price and time to market, for both the component and handset manufacturer.
In modern ASIC design, IC designers must enter the EMI mitigation process at an early stage because switching noise analysis and electrical characterization are important to optimizing the die and package floorplan, as well as layout and substrate design. Electromagnetic compatibility (EMC) and electromagnetic interference (EMI) issues are traditionally addressed, ad hoc, at the chip design level using modern IC design automation (EDA) tools. Because EDA is a semiconductor product design process, it does not adequately address EMC and EMI issues at the board (system) level.
Currently, ASIC designers use their skills and familiarity with EMI generally, to control and minimize electromagnetic coupling (such as crosstalk) at the device and system level by using the commercially available field solvers and built-in constraint managers provided by EDA tools. This process is time consuming and often lacks accuracy when applied to the design and development of complex 3-D ASICs operating at high (greater than about 600 MHz) clock frequencies.
Taking the wireless product as an example, a better solution is to establish a systematic design methodology. Such a methodology must consider noise and interference-related issues at component, PCB, mobile and network level—offering solutions at each stage for their control mitigation both internally and globally.
Even this is often not sufficient because in an actual implementation external interference can contribute to EMI. Such external interference often depends on floor planning, layout and shielding. Traditionally, external interference is addressed experimentally once the prototype becomes available. This is time consuming and costly.
The ultimate (for best performance in the field) floor plan and layout at device or system level cannot be known, a priori, by the semiconductor designer. There are however some general rules and guidelines that are commonly known and understood. For example, it is known that certain blocks of an integrated circuit (IC), such as a baseband processor in a mobile device, can cause interference to either themselves or to other ICs. It is also known that certain blocks of an IC are highly susceptible to interference. When combining a baseband processor with an RF component on a printed circuit board (PCB), the component's emission profiles and/or susceptibility profiles may be known and utilized by known methods to arrive at an electromagnetically compatible configuration for the proposed electronic system.
U.S. Pat. No. 6,834,380, entitled “Automated EMC-Driven Layout and Floor Planning of Electronic Devices and Systems”, commonly assigned as the present application and incorporated herein by reference, describes automated electromagnetic compatibility-driven (EMC-driven) layout and floor planning of electronic devices and systems at the PCB level. The patent describes techniques to account for electromagnetic interactions between circuit components (such as ICs) and to address internal EMC issues at the outset of the design phase. This is done through identification of aggressors and victims and their association to emissions and susceptibility profiles, respectively.
Wireless network operators typically define sensitivity specifications for handsets to ensure optimum service quality. Any improvement in noise sensitivity at the design phase of such handsets makes it easier to meet these strict specifications. Multimode chipsets (e.g., EV-DO, HSPSA, LTE, etc.), and the handsets they go into, are a critical driver to improve noise sensitivity. By looking at the various emissions and susceptibility profiles of components a handset designer is able to deliver a better floor plan, layout and shielding of a PCB—characterized by reduced noise emissions and low EMI. Better EMI performance at the PCB level means less receiver self-jamming with better overall sensitivity.
Known techniques for floor planning and layout design methodology do not take into account the possible network impact when the device is actually operated by a user (for example, in idle, call, and/or data mode). As such, there may be a lack of sensitivity optimization at the handset in its true operating network environment. This is because certain emissions may only be present when the handset is in a particular mode and subject to unique noise metrics from current, voltage or clock switching, occurring in a given state.